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Iterative Multi-user Detection for STBC DS-CDMA Systems in Rayleigh Fading Channels

Iterative Multi-user Detection for STBC DS-CDMA Systems in Rayleigh Fading Channels. Derrick B. Mashwama And Emmanuel O. Bejide. Summary. Investigate performance of Turbo Space-Time Multiuser Receivers Classify such receivers as either Partitioned Approach (PA) or Iterative Approach (IA)

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Iterative Multi-user Detection for STBC DS-CDMA Systems in Rayleigh Fading Channels

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  1. Iterative Multi-user Detection for STBC DS-CDMA Systems in Rayleigh Fading Channels Derrick B. Mashwama And Emmanuel O. Bejide

  2. Summary • Investigate performance of Turbo Space-Time Multiuser Receivers • Classify such receivers as either Partitioned Approach (PA) or Iterative Approach (IA) • Employ Turbo codes for FEC and MIMO techniques to mitigate fading effects • Results: • IA outperforms PA at low SNR • Both schemes are dependent on diversity level, system loading, channel conditions and the detector parameters.

  3. Introduction • Mitigating the effects of Multiple Access Interference (MAI) inherent in CDMA systems • Forward Error Correction in DS-CDMA systems • Multiple-Input Multiple-Output (MIMO) Techniques

  4. Generalized structure of a FEC coded DS-CDMA system in fading channel FEC Encoder Interleaver Multiuser Receiver Scattering Channel FEC Encoder Interleaver Figure 1: FEC Coded Direct Sequence CDMA System in Fading Channels

  5. Mitigating MAI Effects • Optimum MUD • Suboptimal MUDs 1. Linear Detectors - Decorrelator Detector - Minimum Mean Square Error (MMSE) Detector 2. Interference Cancellation Schemes - Parallel Interference Cancellation (PIC) Detector - Successive Interference Cancellation (SIC) 3. Combined Detection Schemes: Zero-Forcing Decision Feedback, Decorrelator/PIC, MMSE/PIC, etc.

  6. Performance of PIC detector in AWGN CDMA Channel AWGN, K=5, PG=15 chips Figure 2: Four Stage PIC BER performance

  7. Forward Error Correction • enables DCS to reduce the amount of erroneous data at the receiver • BER - used as measure of the system performance for given SNR. • Generally FEC codes are classified into: block codes, convolutional codes and Turbo Codes (TC). • A TC is the parallel concatenation of two RSC codes separated by an interleaver.

  8. Turbo Codes Figure 4: Rate r=1/3 Turbo Encoder Structure

  9. MIMO Techniques • Signals propagating through the wireless channel experience path loss and distortion due to multipath fading and additive noise. • Diversity helps improve the receiver performance in the presence of fading. • Diversity Schemes: • Space Diversity • Frequency Diversity • Time Diversity • Polarization Diversity

  10. MIMO Techniques • MIMO Communication systems have been introduced as a viable approach to providing significant performance improvements • Promises high bit rates and improved channel capacity • MIMO signal processing techniques can be divided into two main categories: • Spatial multiplexing (SM) • Space-time codes (STC).

  11. MIMO Signal Processing Techniques Figure 5: Classification of MIMO techniques

  12. Performance of STBC in Fading Channels K=1, Rayleigh Fading Figure 6: BER Performance of BPSK system with no diversity and up to 2x2 transmit diversity for a Rayleigh fading channel

  13. Methodology • Classification of concatenation schemes • Partitioned Approach (PA) • Iterative Approach (IA)

  14. Space-time MUX Space-time MUX Space-time MUX TDp TD1 TD1 TDp TD1 TDp DD 1st PIC Stage pth PIC Stage DD MIMO Matched Filtering DD Turbo Space-Time PA Receiver Figure 7: Turbo Space-Time Partitioned Approach Receiver Structure

  15. TD TD TD Space-time DeMux DD Space-time Mux HDD Space-time DeMux DD Space-time Mux MIMO Matched Filtering MAI Reconstruction HDD DD Space-time DeMux Space-time Mux HDD Turbo Space-Time IA Receiver Figure 8: Turbo Space-Time Approach Receiver Structure

  16. Parameters and Assumptions BPSK Modulation

  17. Parameters and Assumptions • Assume: • Equal power users with perfect power control • Perfect channel state information (CSI) at receiver • Quasi-static channel • No inter-symbol interference (ISI)

  18. Results FIGURE 9: BER Performance vs. SNR for both PA and IA as a functions of increasing iterations. Here, users=4, 2x1 antennas FIGURE 10: BER performance vs. SNR for both PA and IA as a function of diversity. Here, users=4, Iterations=4.

  19. Results FIGURE 11: Performance comparison between PA and IA for different BER vs. SNR system loads. Here Iterations=4,2x2 antennas FIGURE 12: BER performance as a function of system load. Here, SNR =4 and 2x1 antennas

  20. Results FIGURE 13: BER performance as a function of the number of PA and IA iteration. Here, SNR =4, 2x1 antennas

  21. Conclusion • Both PA and IA MUDs achieve considerable capacity gains • At low SNR the IA scheme outperforms PA scheme • As the fidelity of the signal improves PA gradually gains more performance improvements over IA

  22. ?…Q & A…? deemash@crg.ee.uct.ac.za

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